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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
101
Citations
36629
World Ranking
354
National Ranking
42

Liang Gao publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Liang Gao sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 250 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 560 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 721 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Liang Gao D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Liang Gao sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 101 D-Index — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award

Overview

Liang Gao is affiliated with Huazhong University of Science and Technology in China and works primarily in the field of Engineering. Their research spans several subfields including Industrial and Manufacturing Engineering, Civil and Structural Engineering, Artificial Intelligence, Control and Systems Engineering, and Electrical and Electronic Engineering.

The main research topics Liang Gao has focused on include:

  • Scheduling and Optimization Algorithms
  • Advanced Manufacturing and Logistics Optimization
  • Topology Optimization in Engineering
  • Advanced Multi-Objective Optimization Algorithms
  • Assembly Line Balancing Optimization
  • Advanced Battery Technologies Research
  • Manufacturing Process and Optimization

Liang Gao has authored or coauthored research papers published in frequent venues such as:

  • Swarm and Evolutionary Computation
  • Computer Methods in Applied Mechanics and Engineering
  • Journal of Manufacturing Systems
  • SSRN Electronic Journal
  • Robotics and Computer-Integrated Manufacturing

Recent notable papers by Liang Gao include:

  • "An Effective Cooperative Co-Evolutionary Algorithm for Distributed Flowshop Group Scheduling Problems" (2020), published in IEEE Transactions on Cybernetics
  • "A Review on Recent Advances in Vision-based Defect Recognition towards Industrial Intelligence" (2021), published in Journal of Manufacturing Systems
  • "Energy-Efficient Scheduling of Distributed Flow Shop With Heterogeneous Factories: A Real-World Case From Automobile Industry in China" (2020), published in IEEE Transactions on Industrial Informatics
  • "A Surrogate-Assisted Multiswarm Optimization Algorithm for High-Dimensional Computationally Expensive Problems" (2020), published in IEEE Transactions on Cybernetics
  • "Robustly printable freeform thermal metamaterials" (2021), published in Nature Communications

The scientist has collaborated extensively with coauthors including:

  • Xinyu Li
  • Mi Xiao
  • Akhil Garg
  • Weiming Shen
  • Wei Li

Liang Gao has also contributed to several book publications released by Springer Nature, such as:

  • "Isogeometric Topology Optimization" (2022)
  • "Effective Methods for Integrated Process Planning and Scheduling" (2020)
  • "Welding and Cutting Case Studies with Supervised Machine Learning" (2020)
  • "Intelligence Optimization for Green Scheduling in Manufacturing Systems" (2023)

Best Publications

  • A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

    Long Wen;Xinyu Li;Liang Gao;Yuyan Zhang

  • A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis

    Long Wen;Liang Gao;Xinyu Li

  • A transfer convolutional neural network for fault diagnosis based on ResNet-50

    Long Wen;Xinyu Li;Liang Gao

  • An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem

    Guohui Zhang;Xinyu Shao;Peigen Li;Liang Gao

  • An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem

    Xinyu Li;Liang Gao

  • An effective genetic algorithm for the flexible job-shop scheduling problem

    Guohui Zhang;Liang Gao;Yang Shi

  • Energy-efficient permutation flow shop scheduling problem using a hybrid multi-objective backtracking search algorithm

    Chao Lu;Liang Gao;Xinyu Li;Quanke Pan

  • An improved fruit fly optimization algorithm for continuous function optimization problems

    Quan-Ke Pan;Quan-Ke Pan;Hong-Yan Sang;Jun-Hua Duan;Liang Gao

  • Integration of process planning and scheduling-A modified genetic algorithm-based approach

    Xinyu Shao;Xinyu Li;Liang Gao;Chaoyong Zhang

  • Parameter extraction of photovoltaic models using an improved teaching-learning-based optimization

    Shuijia Li;Wenyin Gong;Xuesong Yan;Chengyu Hu

  • Cellular particle swarm optimization

    Yang Shi;Hongcheng Liu;Liang Gao;Guohui Zhang

  • Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem

    Quan-Ke Pan;Quan-Ke Pan;Liang Gao;Ling Wang;Jing Liang

  • A multi-objective genetic algorithm based on immune and entropy principle for flexible job-shop scheduling problem

    Xiaojuan Wang;Liang Gao;Chaoyong Zhang;Xinyu Shao

  • Queuing search algorithm: A novel metaheuristic algorithm for solving engineering optimization problems

    Jinhao Zhang;Mi Xiao;Liang Gao;Quanke Pan

  • A Review on Recent Advances in Vision-based Defect Recognition towards Industrial Intelligence

    Yiping Gao;Xinyu Li;Xi Vincent Wang;Lihui Wang

  • A novel mathematical model and multi-objective method for the low-carbon flexible job shop scheduling problem

    Lvjiang Yin;Xinyu Li;Liang Gao;Chao Lu

  • An adaptive process planning approach of rapid prototyping and manufacturing

    G.Q. Jin;W.D. Li;L. Gao

  • Review on flexible job shop scheduling

    Jin Xie;Liang Gao;Kunkun Peng;Xinyu Li

  • Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning

    Yuyan Zhang;Xinyu Li;Liang Gao;Lihui Wang

  • A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry

    Chao Lu;Liang Gao;Xinyu Li;Shengqiang Xiao

  • An Effective Cooperative Co-Evolutionary Algorithm for Distributed Flowshop Group Scheduling Problems.

    Quan-Ke Pan;Liang Gao;Ling Wang

  • A differential evolution algorithm with self-adapting strategy and control parameters

    Quan-Ke Pan;P. N. Suganthan;Ling Wang;Liang Gao

  • A semi-supervised convolutional neural network-based method for steel surface defect recognition

    Yiping Gao;Liang Gao;Xinyu Li;Xuguo Yan

  • Mathematical modeling and evolutionary algorithm-based approach for integrated process planning and scheduling

    Xinyu Li;Liang Gao;Xinyu Shao;Chaoyong Zhang

Frequent Co-Authors

Xinyu Li
Xinyu Li Huazhong University of Science and Technology
Akhil Garg
Akhil Garg Huazhong University of Science and Technology
Xinyu Shao
Xinyu Shao Huazhong University of Science and Technology
Peigen Li
Peigen Li Huazhong University of Science and Technology
Weidong Li
Weidong Li Wuhan University of Technology
Zhen Luo
Zhen Luo University of Technology Sydney
Chaoyong Zhang
Chaoyong Zhang Huazhong University of Science and Technology
Ling Wang
Ling Wang Tsinghua University
Weiming Shen
Weiming Shen Huazhong University of Science and Technology
Lihui Wang
Lihui Wang Royal Institute of Technology

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